Robust Beamforming Design for IRS-Aided URLLC in D2D Networks

TL;DR

This paper proposes a two-stage IRS-assisted D2D communication protocol to enhance reliability and meet latency constraints in industrial IoT multiuser MISO systems, with optimized beamforming for perfect and imperfect CSI.

Contribution

It introduces a novel IRS-D2D protocol with joint beamforming optimization, improving reliability in IIoT scenarios under various CSI conditions.

Findings

IRS with optimized reflection matrix significantly improves reliability.

D2D communication boosts successful decoding rate.

Protocol maintains reliability despite CSI estimation errors.

Abstract

Intelligent reflecting surface (IRS) and device-to-device (D2D) communication are two promising technologies for improving transmission reliability between transceivers in communication systems. In this paper, we consider the design of reliable communication between the access point (AP) and actuators for a downlink multiuser multiple-input single-output (MISO) system in the industrial IoT (IIoT) scenario. We propose a two-stage protocol combining IRS with D2D communication so that all actuators can successfully receive the message from AP within a given delay. The superiority of the protocol is that the communication reliability between AP and actuators is doubly augmented by the IRS-aided first-stage transmission and the second-stage D2D transmission. A joint optimization problem of active and passive beamforming is formulated, which aims to maximize the number of actuators with successful decoding. We study the joint beamforming problem for cases where the channel state information (CSI) is perfect and imperfect. For each case, we develop efficient algorithms that include convergence and complexity analysis. Simulation results demonstrate the necessity and role of IRS with a well-optimized reflection matrix, and the D2D network in promoting reliable communication. Moreover, the proposed protocol can enable reliable communication even in the presence of stringent latency requirements and CSI estimation errors.